data.table in 5 minutes

Steph Locke

2017-04-20

data.table

data.table basics

Task	How
Read CSV	`irisDT <- fread("iris.csv")`
Return everything	`irisDT irisDT[ ]`
Select columns	`irisDT[ , .(Sepal.Length, Sepal.Width) ]`
Update column	`irisDT[,Sepal.Area:=Sepal.Length*Sepal.Width]`
Restrict rows	`irisDT[ Sepal.Length >=5 , ]`
Aggregate	`irisDT[ , mean(Sepal.Length)]`
Aggregate by group	`irisDT[ , mean(Sepal.Length) , Species ]`
Count	`irisDT[ , .N ]`

data.table awesomeness - IO

qRead<-fread("sample.csv")
## 
Read 76.9% of 13000 rows
Read 13000 rows and 13001 (of 13001) columns from 0.315 GB file in 00:00:13
system.time(
fwrite(qRead,"sample.csv"))
## 
Written 35.9% of 13000 rows in 2 secs using 32 threads. anyBufferGrown=no; maxBuffUsed=49%. Finished in 3 secs.      
                                                                                                                                     
##    user  system elapsed 
##  18.308   2.124   3.415

data.table awesomeness - groups

irisDT<-data.table(iris)
knitr::kable(
  irisDT[, .SD[which.min(Petal.Length)]
       , Species])

Species	Sepal.Length	Sepal.Width	Petal.Length	Petal.Width
setosa	4.6	3.6	1.0	0.2
versicolor	5.1	2.5	3.0	1.1
virginica	4.9	2.5	4.5	1.7